Xiaomi MiMo V2.6 Pro vs Flash: benchmarks, pricing and which to use in BrainBox

MiMo V2.6 Pro and MiMo V2.6 Flash, the models Xiaomi released on September 21, 2026 with open weights under the MIT license, can now be selected in the BrainBox Assistant. Both have a one million token context window and accept images. Pro is the highest scoring open weight model on the Artificial Analysis Intelligence Index as of today; Flash stays close on the agent tests and uses a third of the intelligence units. Both require a plan with full model access.

What are MiMo V2.6 Pro and Flash?

They are two mixture of experts models, or MoE, from Xiaomi's MiMo team, trained in a single reinforcement learning run that mixes thousands of task environments: programming, general agents, visual tasks and cybersecurity, according to the technical report. Xiaomi published the weights on Hugging Face and ModelScope under the MIT license: MiMo-V2.6-Pro-RL and MiMo-V2.6-Flash-RL. Alongside the weights it published the technical report, the training environments, the RL framework and a distilled 9 billion parameter model, MiMo-V2.6-Distill-Qwen-9B. The figures in the table come from the model card and Xiaomi's model page.

In BrainBox, audio and video are not sent to the model: they are transcribed at indexing time and the model receives the transcript with timestamps. The multimodal input it does use is images.

What do the benchmarks say?

Artificial Analysis measures models on its own. MiMo V2.6 Pro scores 46 on the Intelligence Index v4.3, first among the 114 open weight models it has measured, and the same score as Grok 4.7, released the same day. According to the leaderboard, it sits above Grok 4.6 at 44, Gemini 3.8 Flash at 41 and DeepSeek V4.1 Flash at 39, and seven points below Claude Fable 5.1 and GPT-6 Astra, which score 53 in their maximum setting. It generates about 125 tokens per second with 2.19 seconds to first token, and Artificial Analysis calls it "somewhat verbose". Flash has no published score yet.

The agent benchmarks Xiaomi publishes on the model card are the company's own, including the numbers for the closed models, and should be read with that in mind:

Xiaomi's technical report describes "performance comparable to that of frontier models across various domains", and its own table shows where it is not: Claude Opus 5 stays ahead on DeepSWE v1.1, ProgramBench and Terminal Bench 4.0, and the gap on ExploitBench is wide. Pro belongs to the frontier group for agent tasks without leading it, and in BrainBox uses a fraction of the intelligence units Grok 4.7 uses on the same task. Flash stays within 1 to 4 points of Pro on coding and general agent tests; on offensive cybersecurity the distance is larger.

How does the BrainBox Assistant work with MiMo V2.6?

The BrainBox Assistant is an agent. You choose which Boxes and files it may use and which model does the reasoning; the agent decides the steps. Each one shows in the chat: "Listing sources", "Searching documents", "Reading document" with the pages it opened, "Saving note" when it sets something aside for later, and at the end the answer with page citations. With a million tokens of context, MiMo V2.6 can hold many more reads in one conversation before the agent has to compress what it read, and it can read a document of hundreds of pages whole when the task calls for it.

How do you pick them in BrainBox?

1. Check that your plan has full model access

   Xiaomi's models carry the Full plan badge. They appear on paid personal accounts; in a workspace, the admin enables them in the AI policy.

2. Open the Assistant and choose the sources

   In the sidebar you tick the Boxes and files the agent may use. The model picker sits in the bottom bar of the chat and is searchable.

3. Type 'MiMo'

   MiMo V2.6 Pro, MiMo V2.6 Flash and the V2.5 versions appear with their context and badges.

4. Choose Pro or Flash for the task

   Pro to review and reason over a whole case file; Flash for frequent questions and batch summaries.

5. Ask for the task

   If you want a document read whole, say so in the message. Otherwise the agent searches and reads the pages it needs. The answer still carries page citations.

Select model

Select model

MiMo

• 

  MiMo V2.6 ProXiaomi

  Xiaomi flagship, over 1T parameters, for coding, multimodal and long-horizon agentic tasks

  1M contextProFull planImages
• 

  MiMo V2.6 FlashXiaomi

  Open MoE with 309B total and 15B active parameters for coding and long-horizon agent tasks

  1M contextFull planImages

BrainBox is an AI workspace for documents that answers with citations to the exact page. With MiMo V2.6 the answer comes from an open model, and the citation still points to the document in the Box.

How many intelligence units does each task use?

BrainBox does not measure usage in tokens but in intelligence units, and each task uses a different number depending on how many searches and reads the agent makes, how much the model reasons and how much it writes. Estimates for the standard plan, with Grok 4.7 alongside for reference:

These are estimates: a longer answer, more sources or more agent steps push the number up. For reference, the Elite plan includes 400 units a month; with Flash, a case file review uses little more than one question with Grok 4.7.

What happens if the Box is larger than the million token window?

Nothing is left out. The Assistant does not load the whole Box into the model: it searches the selected sources and reads the pages that answer the question, each with its file and page. It works the same for a Box of 200 pages or 20,000. What changes with MiMo V2.6 is how much it can hold as read at once: over a thousand pages before it has to compress what it read into notes.

When does Pro make sense, when Flash, and when neither?

The advantage of these models in BrainBox is context: a million tokens with no usage cliff. With Grok 4.7 a single step over about 300 pages nearly doubles the units it uses; with Xiaomi's models usage grows evenly up to the limit.

How is this different from using MiMo in Xiaomi's app?

Xiaomi offers the models in its AI Studio, MiMo Code, MiMo Desktop and its API, according to the model card. There you work with what you paste into the conversation. In BrainBox the model works on the Box.

A research team can upload a hundred papers, pick Flash for exploratory questions and move to Pro for the final analysis, checking each citation in the same panel. The rest of the document workspace does not change with the model.

According to the technical report, the reinforcement learning phase cost $2.6 million for Pro and $0.9 million for Flash, with batches of 1,568 prompts and sequences of 110,000 to 150,000 tokens. In BrainBox, reading a 450 page case file whole in a single pass uses about 14 intelligence units with Pro and 6 with Flash.

Sources

• Xiaomi MiMo, model cards for MiMo-V2.6-Pro-RL and MiMo-V2.6-Flash-RL on Hugging Face: parameters, context, modalities, MIT license, benchmark table and availability.
• Xiaomi MiMo, MiMo-V2.6 technical report: reinforcement learning, RL cost, distilled model and open suite.
• Xiaomi, MiMo-V2.6-Pro model page: 128K maximum output and modalities.
• Artificial Analysis, MiMo-V2.6-Pro: Intelligence Index, rank among open weight models, speed and latency.
• Artificial Analysis, model leaderboard: scores for Grok 4.7, Grok 4.6, Gemini 3.8 Flash, DeepSeek V4.1 Flash, Claude Fable 5.1, GPT-6 Astra and MiMo-V2.5-Pro.